@article{ade98e7ac9ce456a8835d9a08084c436,
title = "Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen",
abstract = "The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca's large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells.",
keywords = "ANDROGEN RECEPTOR, BREAST-CANCER, GENE, CELL, INHIBITION, RESISTANCE, PATHWAY, MUTATIONS, LANDSCAPE, RESOURCE",
author = "Menden, {Michael P.} and Dennis Wang and Mason, {Mike J.} and Bence Szalai and Bulusu, {Krishna C.} and Yuanfang Guan and Thomas Yu and Jaewoo Kang and Minji Jeon and Russ Wolfinger and Tin Nguyen and Mikhail Zaslavskiy and Jang, {In Sock} and Zara Ghazoui and Ahsen, {Mehmet Eren} and Robert Vogel and Neto, {Elias Chaibub} and Thea Norman and Tang, {Eric K. Y.} and Garnett, {Mathew J.} and {Di Veroli}, {Giovanni Y.} and Stephen Fawell and Gustavo Stolovitzky and Justin Guinney and Dry, {Jonathan R.} and Julio Saez-Rodriguez and Jordi Abante and Abecassis, {Barbara Schmitz} and Nanne Aben and Delasa Aghamirzaie and Tero Aittokallio and Akhtari, {Farida S.} and Bissan Al-lazikani and Tanvir Alam and Amin Allam and Chad Allen and {de Almeida}, {Mariana Pelicano} and Doaa Altarawy and Vinicius Alves and Alicia Amadoz and Benedict Anchang and Antolin, {Albert A.} and Ash, {Jeremy R.} and Remzi Celebi and Michel Dumontier and Friederike Ehrhart and Chris Evelo and Miller, {Ryan A.} and Linda Rieswijk and Egon Willighagen and {AstraZeneca-Sanger Drug Combination DREAM Consortium}",
note = "Funding Information: We thank the Genomics of Drug Sensitivity in Cancer and COSMIC teams at the Wellcome Trust Sanger Institute for help with the preparation of the molecular data, Denes Turei for help with Omnipath, and Katjusa Koler for help with matching drug names across combination screens. We thank AstraZeneca for funding and provision of data to the DREAM Consortium to run the challenge, and funding from the European Union Horizon 2020 research (under grant agreement No 668858 PrECISE to J.S.R.), the Joint Research Center for Computational Biomedicine (which is partially funded by Bayer AG) to J.S.R., National Institute for Health Research (NIHR) Sheffield Biomedical Research Center, Premium Postdoctoral Fellowship Program of the Hungarian Academy of Sciences. M.G lab is supported by Wellcome Trust (102696 and 206194). Funding Information: Competing interests: K.C.B., Z.G., G.Y.D., E.K.Y.T., S.F., and J.R.D. are AstraZeneca employees. K.C.B., Z.G., E.K.Y.T., S.F., and J.R.D. are AstraZeneca shareholders. Y.G. receives personal compensation from Eli Lilly and Company, is a shareholder of Cleerly, Inc., and Ann Arbor Algorithms, Inc. M.G. receives research funding from AstraZeneca and has performed consultancy for Sanofi. The remaining authors declare no competing interests. Publisher Copyright: {\textcopyright} 2019, The Author(s).",
year = "2019",
month = jun,
day = "17",
doi = "10.1038/s41467-019-09799-2",
language = "English",
volume = "10",
journal = "Nature Communications",
issn = "2041-1723",
publisher = "Nature Publishing Group",
number = "1",
}